How to Apply to AssemblyAI

Key Takeaways

Before applying, use AssemblyAI's API yourself — sign up for their free tier, transcribe an audio file, try their LeMUR LLM features, and reference this hands-on experience in your application to demonstrate genuine product familiarity
Tailor your resume to the exact role using keywords from the job listing, and ensure your PDF is cleanly parsed by Greenhouse by testing it with a free resume parser tool before submitting
Prepare for technically deep interviews by reviewing recent advances in speech recognition, transformer architectures, and the specific technologies listed in your target role (Go, PyTorch, Kubernetes, etc.)
Emphasize scale metrics and production ownership in every resume bullet and interview answer — AssemblyAI needs people who've built systems that handle real-world volume, not just coursework or Kaggle projects
Research AssemblyAI's published blog posts (assemblyai.com/blog) and any papers from their research team to speak knowledgeably about their technical approach during interviews
In your cover letter or application notes, articulate specifically why speech AI excites you — hiring managers at mission-driven startups can immediately distinguish genuine enthusiasm from template applications

About AssemblyAI

AssemblyAI builds state-of-the-art AI models for speech recognition, speaker understanding, and audio intelligence, delivering them as simple, production-ready APIs that developers integrate in minutes. Founded by Dylan Fox, the company has raised significant venture capital and positioned itself as one of the most technically ambitious startups in the speech AI space — competing directly with offerings from Google, AWS, and OpenAI by consistently pushing the boundaries of model accuracy and capability. Their products power transcription, summarization, sentiment analysis, and LLM-based audio understanding for thousands of companies ranging from early-stage startups to Fortune 500 enterprises. What makes AssemblyAI distinct is its research-first DNA paired with a developer-obsessed product philosophy. The company employs researchers who publish at top-tier conferences (NeurIPS, ICML, Interspeech) alongside engineers who translate those breakthroughs into APIs developers actually enjoy using. This is not a company that wraps someone else's model in an API — they train their own foundational speech models from scratch, which is an extraordinarily rare commitment for a company of their size. AssemblyAI operates as a remote-first organization, attracting talent globally while maintaining a tight-knit, high-caliber team. The culture emphasizes intellectual curiosity, ownership, and velocity — employees frequently describe it as the rare environment where cutting-edge research and production-grade engineering coexist. With active roles spanning Applied AI, Machine Learning research, Go engineering for their LLM team, and technical customer-facing positions, AssemblyAI is scaling thoughtfully, hiring specialists who can operate with autonomy and push the entire field of speech AI forward.

Application Process

1
Identify the Right Role on AssemblyAI's Careers Page
Visit assemblyai.com/careers to browse their currently open positions, which typically number under 15 — reflecting their deliberate, quality-over-quantity hiring philosophy. Read each job description carefully; AssemblyAI roles are highly specific (e.g., 'Senior Software Engineer, Go - LLM Team' versus 'Senior Software Engineer, AI Data'), and applying to the wrong one signals a lack of attention. Note any timezone or location requirements, as some roles specify EST or EMEA availability despite the remote-first structure.
2
Submit Your Application Through Greenhouse
All applications funnel through AssemblyAI's Greenhouse-powered portal. You'll upload your resume (PDF strongly recommended for parsing accuracy), fill in required fields, and typically have the option to include a cover letter or links to your GitHub, portfolio, or published research. Because AssemblyAI is a small team hiring specialists, every application receives genuine human review — but only after passing Greenhouse's initial parsing and keyword screening.
3
Recruiter Screen (30-45 Minutes)
Candidates who clear the initial review typically receive a recruiter screen focused on your background, motivations, and alignment with AssemblyAI's mission in speech AI. Expect pointed questions about why you're interested in audio/speech technology specifically, your experience with relevant technical domains, and your comfort operating in a fast-moving startup environment. This is also where logistical details like timezone overlap, compensation expectations, and start date are typically discussed.
4
Technical Assessment or Take-Home Challenge
Depending on the role, you'll encounter either a live technical screen or a take-home project. Engineering roles commonly involve systems design or coding challenges relevant to AssemblyAI's stack (Go, Python, distributed systems, ML pipelines). Research roles may involve discussing a published paper or working through a model architecture problem. Applied AI and support engineering roles often include practical scenarios involving API debugging or customer-facing technical problem-solving.
5
Team Interviews (2-3 Sessions)
The core interview loop typically involves two to three sessions with team members you'd work alongside — engineers, researchers, or cross-functional partners depending on the role. At a company of AssemblyAI's size, you'll likely meet people who are deeply embedded in the work, so expect technically dense conversations rather than generic behavioral questions. For senior roles, at least one session commonly explores system architecture decisions, trade-off reasoning, and how you'd approach problems at AssemblyAI's specific scale.
6
Hiring Manager or Leadership Conversation
Final-stage candidates typically meet with the hiring manager and potentially a member of AssemblyAI's leadership team. This conversation tends to focus on culture fit, ownership mentality, and your long-term vision for the domain. Given AssemblyAI's emphasis on hiring people who drive entire areas of the product or research forward, expect questions about how you prioritize independently and how you've handled ambiguity in previous roles.
7
Offer and Onboarding
AssemblyAI typically moves quickly from final interview to offer — often within one to two weeks. Offers commonly include competitive base salary, equity, and comprehensive benefits reflecting their well-funded startup status. Onboarding for remote employees is reportedly structured with clear ramp-up plans, early pairing with team members, and access to internal documentation and model training infrastructure from day one.

Resume Tips for AssemblyAI

critical

Lead with Speech AI, NLP, or Audio Domain Experience

AssemblyAI is not a generalist tech company — they're building foundational speech models. If you have any experience with ASR (automatic speech recognition), NLP, audio signal processing, language models, or real-time transcription systems, elevate it to the top third of your resume. Even tangentially related work, like building data pipelines for audio datasets or deploying ML models at scale, should be framed in terms relevant to speech AI. A candidate who mentions 'built an audio preprocessing pipeline handling 10M+ utterances' will immediately resonate more than someone listing generic backend experience.

critical

Showcase Your Specific Tech Stack Alignment

AssemblyAI's engineering roles frequently reference Go, Python, PyTorch, Kubernetes, and distributed systems. Their LLM team roles specifically call for Go expertise. Don't bury these keywords in a skills section — weave them into your experience bullets with measurable outcomes. For example: 'Designed and deployed a Go-based microservice processing 50K concurrent audio streams with sub-200ms latency.' Greenhouse's parsing will pick up these terms, and human reviewers at a company this size will immediately see stack alignment.

critical

Quantify Scale and Performance Metrics

AssemblyAI processes enormous volumes of audio data and serves latency-sensitive APIs to thousands of customers. Resumes that quantify scale — requests per second, data volumes, model inference latency, uptime percentages, pipeline throughput — demonstrate you've operated at the kind of performance thresholds they care about. Vague statements like 'improved system performance' carry no weight compared to 'reduced model inference latency by 40% while maintaining 99.9% accuracy on a 1B-parameter speech model.'

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Highlight Published Research or Open-Source Contributions

AssemblyAI's research team publishes at top venues, and their engineering culture values people who engage with the broader ML community. If you've published papers (especially in speech, audio, or language modeling), contributed to open-source ML frameworks, or maintain a technical blog, create a dedicated section for this. Link directly to papers, repos, or posts. For the Senior Researcher role in particular, your publication record and research impact will likely be weighted as heavily as your industry experience.

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Demonstrate Remote-First Autonomy and Ownership

As a remote-first company with a lean team, AssemblyAI hires people who can drive projects independently without constant oversight. Your resume should include examples of owning end-to-end projects: scoping, building, shipping, and iterating. Use language like 'led,' 'owned,' 'initiated,' and 'shipped' rather than 'assisted,' 'participated,' or 'contributed to.' At least two or three bullets should convey that you identified a problem and solved it without being told exactly what to do.

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Keep It to One Page (Two Maximum for Senior/Research Roles)

With only nine open roles and a small hiring team, reviewers at AssemblyAI are reading every resume carefully but quickly. A concise, one-page resume signals that you can prioritize and communicate efficiently — qualities essential in a startup. Senior engineers and researchers with 10+ years of experience or substantial publication lists may justify two pages, but only if every line directly supports your candidacy for the specific role. Remove anything older than 8-10 years unless it's directly relevant to speech AI or ML.

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Tailor Your Resume to the Exact Role Title

AssemblyAI's open roles are highly differentiated — a Senior Software Engineer on the LLM Team needs different emphasis than a Senior Support Engineer or Applied AI Engineer. Mirror the job description's language in your resume. If the listing mentions 'LLM orchestration,' 'customer-facing debugging,' or 'production ML systems,' use those exact phrases where truthful. Greenhouse ranks keyword relevance, and human reviewers at domain-specific companies like AssemblyAI can immediately tell when a resume was tailored versus sent generically.

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Include a Two-Line Professional Summary Tied to AssemblyAI's Mission

Open your resume with a brief summary that connects your expertise to what AssemblyAI specifically does. Something like: 'ML engineer with 6 years of experience building and deploying speech recognition models at scale, specializing in transformer-based architectures and real-time audio processing pipelines.' This immediately contextualizes everything that follows and tells the Greenhouse reviewer — human or automated — that you're not applying to every open ML role on the internet.

ATS System: Greenhouse

Greenhouse is the industry-standard ATS used by high-growth startups and mid-market companies. It parses uploaded resumes into structured data fields, scores candidates based on configurable criteria, and enables hiring teams to manage pipeline stages collaboratively. At a company like AssemblyAI with a small number of open roles, Greenhouse likely serves more as an organizational tool than a high-volume filtering system — but proper formatting still determines whether your experience is parsed correctly and presented cleanly to reviewers.

Upload your resume as a PDF to preserve formatting while maintaining Greenhouse's ability to parse text — avoid image-based PDFs or heavily designed templates with columns and text boxes
Use standard section headers (Experience, Education, Skills, Publications) because Greenhouse's parser maps content to fields based on expected headings
Include the exact job title keywords from the posting (e.g., 'Go,' 'LLM,' 'speech recognition,' 'API infrastructure') in your experience bullets, not just a skills list
Fill out every field in the Greenhouse application form completely — partially completed applications are frequently deprioritized in the review queue
If the application includes optional fields for GitHub, LinkedIn, or portfolio links, always fill them in; at a developer-tools company like AssemblyAI, these carry meaningful weight
Avoid using headers/footers for critical information like contact details, as Greenhouse's parser sometimes skips content in these regions
Use straightforward date formatting (Month Year – Month Year) for each role to ensure Greenhouse correctly calculates your years of experience

Complete Greenhouse Resume Guide →

Interview Culture

AssemblyAI's interview process reflects its identity as a research-driven, engineering-first startup: expect technical depth over corporate formality.

Interviews are commonly conducted via video call, consistent with their remote-first culture, and the overall process typically spans two to four weeks from application to offer — faster than most companies of comparable technical ambition. The technical assessment is where AssemblyAI differentiates itself from generic startup interviews. For engineering roles, you should prepare for systems design discussions centered on real problems in speech AI infrastructure: how would you design a low-latency streaming transcription pipeline? How would you architect an LLM-based summarization system that scales to millions of API calls daily? For the Go-focused LLM team role, expect live coding or architecture discussions in Go specifically. Research candidates should be ready to present their work, discuss recent papers in speech and language modeling, and whiteboard novel approaches to problems like speaker diarization, word error rate reduction, or efficient transformer inference. Culture fit at AssemblyAI signals something specific: intellectual humility combined with a bias toward action. Interviewers commonly probe for how you handle disagreements in technical direction, how you make decisions with incomplete information, and whether you default to shipping and iterating or over-planning. The team values people who are genuinely passionate about the problem space — not just looking for any ML role, but specifically excited about making speech AI more accurate, accessible, and useful. You'll likely interact with three to five people throughout the process, including your potential direct manager and at least one peer-level team member. Because the team is small, every hire significantly shapes the company's trajectory, so interviewers are evaluating whether they'd want to collaborate with you daily on hard problems. Come prepared to ask thoughtful questions about their model architecture decisions, research roadmap, or API design philosophy — this signals genuine engagement with what makes AssemblyAI unique in a crowded AI landscape.

What AssemblyAI Looks For

Deep technical expertise in speech AI, NLP, machine learning, or distributed systems — not generalist 'full-stack' breadth, but real depth in domains relevant to their product
Demonstrated ability to ship production-quality systems, not just prototypes or research code — they need people who bridge the gap between research breakthroughs and reliable APIs
Strong alignment with their specific mission of making speech AI accessible via developer-friendly APIs, evidenced by genuine interest in the problem space
Self-directed ownership mentality suited to a remote-first startup where you'll be trusted to drive entire workstreams with minimal hand-holding
Track record of working at scale — processing large datasets, serving high-throughput APIs, training large models — commensurate with the infrastructure challenges of real-time speech processing
Intellectual curiosity and willingness to engage with cutting-edge research, whether by publishing, contributing to open source, or staying current with developments in speech and language modeling
Clear, precise communication skills — essential in a remote environment where async written communication is the primary mode of collaboration across timezones

Frequently Asked Questions

How long does AssemblyAI's hiring process typically take from application to offer?

Based on patterns common at well-organized startups using Greenhouse, the process from application to offer typically takes two to four weeks. The initial recruiter screen usually happens within one week of application review, with technical and team interviews scheduled across the following one to two weeks. Because AssemblyAI has a relatively small number of open roles and a focused team, scheduling tends to be more efficient than at large companies — but timelines can extend if the role requires specialized assessments or if there's significant timezone coordination needed for their globally distributed team.

Does AssemblyAI require a cover letter with my application?

Greenhouse typically presents the cover letter as an optional field for AssemblyAI's applications. However, given that they hire fewer than a dozen roles at a time and each hire carries significant weight, submitting a targeted cover letter is strongly recommended. Use it to explain your specific interest in speech AI (not just 'AI in general'), reference a particular AssemblyAI product feature or research paper that excites you, and briefly describe how your experience maps to the role's core challenges. A three-paragraph cover letter that demonstrates you've actually used their product will stand out dramatically from the majority of applicants who skip it.

Can I apply to multiple roles at AssemblyAI simultaneously?

Greenhouse supports multiple applications, and it's technically possible to apply to more than one role. However, at a small company like AssemblyAI where the hiring team likely overlaps across roles, applying to several positions can signal uncertainty about your direction. If you genuinely qualify for two closely related roles (e.g., Senior Software Engineer on two different teams), it's better to apply to the one that's the strongest fit and mention your interest in the other during the recruiter screen. The recruiter can then route you appropriately based on team needs and your profile.

What should I prepare for a technical interview at AssemblyAI?

Preparation should be role-specific and grounded in AssemblyAI's actual product domain. For software engineering roles, review distributed systems design (particularly real-time streaming architectures), Go or Python depending on the team, and API design patterns — think about how you'd build a transcription service handling thousands of concurrent audio streams. For ML and research roles, be ready to discuss transformer architectures, speech recognition fundamentals (CTC, attention-based models, word error rate optimization), and your experience training models on large datasets. For all roles, study AssemblyAI's blog and documentation to understand their product capabilities, and be prepared to discuss trade-offs you've made in production systems.

Does AssemblyAI hire fully remote employees, and are there location restrictions?

AssemblyAI operates as a remote-first company and has historically hired talent across multiple locations. However, specific roles often include timezone requirements — you'll notice listings specifying 'EST' or 'EMEA' availability, which indicates the team's collaboration hours. Read the job description carefully for any geographic or timezone constraints before applying. Even for roles without explicit location requirements, be prepared to discuss your availability for synchronous collaboration during the recruiter screen, as real-time coordination remains important for a small, fast-moving team.

What level of experience does AssemblyAI expect for their open roles?

AssemblyAI's current openings skew toward senior-level positions — Senior Software Engineer, Senior Researcher, Senior Support Engineer, and Senior Technical Account Manager. This reflects their stage as a funded startup that needs experienced operators who can contribute immediately without extensive ramp-up. Most roles likely expect five or more years of relevant experience, with research positions potentially requiring a PhD or equivalent publication track record. The Applied AI Engineer role may have a somewhat broader experience range, but candidates should still bring meaningful hands-on experience with ML systems in production rather than purely academic backgrounds.

How can I make my application stand out at a competitive AI startup like AssemblyAI?

Three things separate memorable applications from the pile at companies like AssemblyAI. First, demonstrate product familiarity — sign up for their API, run a transcription, try their audio intelligence features, and reference specific observations in your application. Second, show domain depth rather than breadth; a portfolio project involving speech recognition, audio processing, or language model fine-tuning is worth more than ten generic web apps. Third, if you have public technical writing, open-source contributions, or published research, make them impossible to miss by linking them prominently. AssemblyAI's team actively participates in the research and developer community, so a well-crafted blog post about ASR accuracy benchmarking or a PR to a popular ML library can carry weight equivalent to a strong cover letter.

What ATS tips are most important for getting past Greenhouse at AssemblyAI?

Since AssemblyAI has a small volume of applications relative to large enterprises, Greenhouse functions more as an organizational system than a mass-filtering tool — your resume will likely receive human review. That said, clean parsing is still critical so your information displays correctly to reviewers. Submit a single-column PDF with standard section headers, use the exact technical terms from the job listing (e.g., 'Go,' 'LLM,' 'real-time streaming,' 'speech recognition'), and ensure all Greenhouse form fields are completed fully. Include links to your GitHub, LinkedIn, and any relevant portfolios in the designated fields. Avoid tables, multi-column layouts, graphics, or unusual fonts that could cause Greenhouse's parser to scramble your content.

Should I follow up after submitting my application to AssemblyAI?

A single, thoughtful follow-up is appropriate if you haven't heard back within two weeks of applying. Given AssemblyAI's remote-first culture, email is the preferred channel — look for the recruiter's contact information on LinkedIn or the company's team page. Keep the follow-up concise: reiterate your interest in the specific role, mention one concrete reason you're excited about AssemblyAI's work (referencing a recent product launch or blog post works well), and ask if there's any additional information you can provide. Avoid following up more than once, and never reach out via multiple channels simultaneously — at a small company, persistence can quickly become intrusion.

Sample Open Positions

Check Your Resume Before Applying → View 7 open positions at AssemblyAI

Related Resources

Similar Companies

Sources

AssemblyAI Careers Page — AssemblyAI
AssemblyAI Company Blog and Research — AssemblyAI
Greenhouse ATS Candidate Help & Resume Parsing Documentation — Greenhouse Software
AssemblyAI Glassdoor Reviews and Interview Insights — Glassdoor